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DISCRIMINANT ANALYSIS OF MULTI-DIMENSIONAL INTERVAL DATA AND ITS APPLICATION TO CHEMICAL SENSING

โœ Scribed by ISHIBUCHI, HISAO; TANAKA, HIDEO; FUKUOKA, NORIKO

Book ID
126670379
Publisher
Taylor and Francis Group
Year
1990
Tongue
English
Weight
543 KB
Volume
16
Category
Article
ISSN
0308-1079

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Many pattern recognition applications involve the treatment of high-dimensional data and the small sample size problem. Principal component analysis (PCA) is a common used dimension reduction technique. Linear discriminate analysis (LDA) is often employed for classification. PCA plus LDA is a famous